Google announced Global Signal Exchange, a new project to facilitate the collection and sharing of data related to online scams and fraud. While the company is already blocking millions of attempted scams daily across all its products and services, this project will provide organizations with the necessary information they need to identify and block scams.
“We know from experience that fighting scams and the criminal organizations behind them requires strong collaboration among industry, businesses, civil society and governments to combat bad actors and protect users,” Amanda Storey, senior director of trust and safety at Google, and Nafis Zebarjadi, product manager of account security at Google, wrote in a post announcing the project.
Google is partnering with Global Anti-Scam Alliance and DNS Research Foundation to launch GSE. The new project will benefit from GASA’s extensive network of stakeholders and expand on DNS Research Federation’s robust data platform with already over 40 million fraud signals. The company is providing the funding to launch GSE and will hold the centralized data engine on Google Cloud, the company said.
Participants will be able to share and ingest signals, while leveraging AI to find patterns and match signals. GASA and DNS Research Federation will manage access for qualifying organizations.
As part of a pilot program, GSE was able to share over 100,000 URLs of bad merchants and receive roughly one million signals. The company plans to start by sharing Google Shopping URLs that have already been flagged as scams, and then eventually add data from other product areas.
“By joining forces and establishing a centralized platform, GSE aims to improve the exchange of abuse signals, enabling faster identification and disruption of fraudulent activities across various sectors, platforms and services,” the company said.
https://eu-images.contentstack.com/v3/assets/blt6d90778a997de1cd/blt9b0beda929381eae/6707c8eb8c138c40a3829bc3/Fraud_photobyphotoboy_Adobe.jpg?disable=upscale&width=1200&height=630&fit=crop
